Parallel Clustered Mesh Simplification with Quantifiable Error for Unified Mesh Representations in Rasterization and BVH-Based Digital Twin Simulations

Digital Twins exhibit heterogeneous spatial accuracy requirements across simulation domains. Spatial error–driven Level of Detail schemes exist for rasterization but are not directly applicable to Bounding Volume Hierarchy–traversal algorithms, such as ray tracing or collision detection. This work introduces a unified detail hierarchy that supports both algorithmic paradigms. We integrate clustered triangle mesh representations (meshlets) with multi-attribute mesh simplification while tracking approximation error per cluster. We present a specialized Quadric Error Metric that accurately captures the spatial error required for Digital Twin simulations. Additionally, we propose a unified clustering method that balances the spatial requirements for low Surface Area Heuristic in Bounding Volume Hierarchy traversal with the topological and fullness constraints necessary for rasterization, enabling a single cluster representation. We further introduce a method to integrate clusters from all Levels of Detail with spatial error into a single Bounding Volume Hierarchy by alternating construction priorities between spatial error and Surface Area Heuristic at consecutive levels. This mitigates excessive overlap from stacked clusters and improves pruning during traversal. The method is highly parallelizable and exhibits scalability on both CPUs and GPUs. Experiments demonstrate substantial geometry pruning within spatial error thresholds, yielding significant computational savings while maintaining accuracy requirements.